plotly

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.5     ✓ purrr   0.3.4
## ✓ tibble  3.1.4     ✓ dplyr   1.0.7
## ✓ tidyr   1.1.3     ✓ stringr 1.4.0
## ✓ readr   2.0.1     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(p8105.datasets)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
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library(ggridges)
library(flexdashboard)

data("rest_inspec")
head(rest_inspec)

## # A tibble: 6 × 18
##   action         boro   building  camis critical_flag cuisine_descrip… dba      
##   <chr>          <chr>  <chr>     <int> <chr>         <chr>            <chr>    
## 1 Violations we… MANHA… 425      4.15e7 Not Critical  Italian          SPINELLI…
## 2 Violations we… MANHA… 37       4.12e7 Critical      Korean           SHILLA K…
## 3 Violations we… MANHA… 15       4.11e7 Not Critical  Café/Coffee/Tea CITY PERK
## 4 Violations we… MANHA… 35       4.13e7 Critical      Korean           MADANGSUI
## 5 Violations we… MANHA… 1271     5.00e7 Critical      American         THE HARO…
## 6 Violations we… MANHA… 155      5.00e7 Not Critical  Donuts           DUNKIN D…
## # … with 11 more variables: inspection_date <dttm>, inspection_type <chr>,
## #   phone <chr>, record_date <dttm>, score <int>, street <chr>,
## #   violation_code <chr>, violation_description <chr>, zipcode <int>,
## #   grade <chr>, grade_date <dttm>

## filter or randomly sample from the complete dataset
rest_inspec_df = 
  rest_inspec %>%
  select(boro,critical_flag,cuisine_description,score,grade) %>%
  filter(!is.na(score),!is.na(grade),cuisine_description=="Italian") 

## boxplot
box_df = 
rest_inspec_df %>% 
  ggplot(aes(x = boro, y = score, fill = boro)) +
  geom_boxplot() +
  theme(axis.text.x = element_text(angle = 90, hjust = 1))
 ggplotly(box_df)